AI Consulting for Airlines
Strategy, custom AI implementation, and team enablement — delivered by airline AI operators, not generalists. We have built the AI that runs airlines. Now we help you build yours.
How we engage
A structured path from "we should be using AI" to AI running in production with your team operating it.
Three practices, one team
AI Strategy & Roadmap
Fractional Chief AI Officer engagements, AI roadmaps tied to operational KPIs, ROI modelling, vendor selection, and governance frameworks. For airlines that need AI direction before AI code.
Custom AI Implementation
Bespoke models built and deployed in your environment: predictive maintenance, computer vision (turn analysis, ramp safety, defect detection), ops AI agents, demand forecasting, dynamic pricing, and operational decision support.
Training & Enablement
AI literacy programs for leadership, hands-on sessions for engineering and data teams, and ops-floor enablement for crew, dispatch, OCC, and safety. Build internal capability so the AI keeps working after we leave.
AI Governance & Safety
Policies, model risk management, EASA/FAA-aware AI governance, audit trails, and human-in-the-loop frameworks. Ship AI in regulated operations without becoming the cautionary tale.
Data & Platform Foundations
Most AI failures are data failures. We audit your data estate, design pipelines, and stand up the platform foundations (lakehouse, feature store, MLOps) that make every AI initiative downstream cheaper and faster.
Embedded AI Teams
For airlines that want their own AI capability long-term, we embed senior AI engineers and ML scientists alongside your team. We hire, train, and hand over — leaving you with talent, not a dependency.
Even our consulting practice runs on AI.
From day one, we apply our own platform's intelligence to your engagement — analyzing your operational data, generating personalized recommendations for your team, and surfacing the items that need attention before the next steering meeting.
Reads your data on day one, not month three
From kickoff, we ingest your operational data — ops, crew, safety, finance — and apply our own analytical models to surface the highest-leverage AI opportunities. No 12-week discovery phase before the first insight.
A roadmap calibrated to your fleet, network, and team
Recommendations are tied to your specific KPIs, fleet composition, network shape, and existing tech debt. Not a deck of generic AI use cases — a sequenced plan for your operation, with effort, cost, and ROI for each move.
Predicts the impact before you commit the budget
We model the operational and financial impact of each AI initiative against your historical data — so the business case is grounded in your numbers, not industry averages. Then we measure actual lift against the forecast as we ship.
Attention Required Across The Engagement
A live feed of items the engagement team has prioritized — example of what we surface for clients each week.
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Predictive maintenance pilot for B737NG: estimated $4.2M annual savings, 11-month payback — recommended as the first production deployment.
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Data quality gap detected in turn-time logs across 4 stations — blocks the OTP forecasting initiative until resolved. Remediation plan attached.
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Vendor pitch from "AI for airlines" provider does not match your data reality — independent assessment shows 40% of claimed features unsupportable on your dataset.
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Internal AI literacy workshop completed for 38 ops leaders — pre/post knowledge lift +52%, 7 leaders identified as AI champions for next phase.
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3 quick-win automations shipped in week 4 — saving an estimated 280 analyst-hours per quarter while the larger ML initiatives are still being built.
Talk to airline AI operators
Not a sales call — a working session. Bring a problem; we will tell you what AI can and cannot do about it, with the honesty only operators can.
Book a Working Session